Experiment design for MPC relevant identification. - R. Bhushan Gopaluni; R. S. Patwardhan; Sirish L. Shah (ACC, 2002)

The nature of data pre-filters in MPC relevant identification - open- and closed-loop issues. - R. Bhushan Gopaluni; R. S. Patwardhan; S. L. Shah 001 (Autom., 2003)

Identification of Symmetric Noncausal Processes: Cross-Directional Response Modelling of Paper Machines. - R. Bhushan Gopaluni; Philip D. Loewen; Mohammed Ammar; Guy Albert Dumont; Michael S. Davies (CDC, 2006)

Adaptive signal processing of asset price dynamics with predictability analysis. - Rogemar S. Mamon; Christina Erlwein; R. Bhushan Gopaluni (Inf. Sci., 2008)

Energy optimization in a pulp and paper mill cogeneration facility. - Devin J. Marshman; Terrance Chmelyk; M. S. Sidhu; R. Bhushan Gopaluni; Guy Albert Dumont (ACC, 2010)

Development of a physiological model forpatients with type 2 diabetes mellitus. - O. Vahidi; K. E. Kwok; R. Bhushan Gopaluni; L. Sun (ACC, 2010)

Detection of organ dysfunction in type II diabetic patients. - O. Vahidi; R. Bhushan Gopaluni; K. E. Kwok (ACC, 2011)

Constrained dual ensemble Kalman filter for state and parameter estimation. - Vinay A. Bavdekar; Jagdeesan Prakash; Sirish L. Shah; R. Bhushan Gopaluni (ACC, 2013)

Optimal control and state estimation of lithium-ion batteries using reformulated models. - Bharatkumar Suthar; Venkatasailanathan Ramadesigan; Paul W. C. Northrop; R. Bhushan Gopaluni; Shriram Santhanagopalan; Richard D. Braatz; Venkat R. Subramanian 001 (ACC, 2013)

A Particle Filter Approach to Approximate Posterior Cramer-Rao Lower Bound: The Case of Hidden States. - Aditya Tulsyan; Biao Huang 001; R. Bhushan Gopaluni; J. Fraser Forbes (IEEE Trans. Aerosp. Electron. Syst., 2013)

Sensitivity of MIMO controller performance to model-plant mismatch, with applications to paper machine control. - Mahdi Yousefi; Michael G. Forbes; R. Bhushan Gopaluni; Philip D. Loewen; Guy Albert Dumont; Johan U. Backström (CCA, 2014)

Sparse identification in chemical master equations for monomolecular reaction networks. - Kwang Ki Kevin Kim; Hong Jang; R. Bhushan Gopaluni; Jay H. Lee; Richard D. Braatz (ACC, 2014)

Sensitivity of controller performance indices to model-plant mismatch: An application to paper machine control. - Mahdi Yousefi; Michael G. Forbes; R. Bhushan Gopaluni; Guy Albert Dumont; Johan U. Backström; Ashish Malhotra (ACC, 2014)

Cross-directional controller performance monitoring for paper machines. - Qiugang Lu; Lee D. Rippon; R. Bhushan Gopaluni; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont (ACC, 2015)

Real-time model predictive control for the optimal charging of a lithium-ion battery. - Marcello Torchio; Nicolas A. Wolff; Davide Martino Raimondo; Lalo Magni; Ulrike Krewer; R. Bhushan Gopaluni; Joel A. Paulson; Richard D. Braatz (ACC, 2015)

Detecting model-plant mismatch without external excitation. - Mahdi Yousefi; Qiugang Lu; R. Bhushan Gopaluni; Philip D. Loewen; Michael G. Forbes; Guy Albert Dumont; Johan U. Backström (ACC, 2015)

Model-based detection of organ dysfunction and faults in insulin infusion devices for type 2 diabetic patients. - Melissa Barazandegan; K. Ezra Kwok; R. Bhushan Gopaluni (ACC, 2016)

Economic nonlinear model predictive control for mechanical pulping processes. - Hui Tian; Qiugang Lu; R. Bhushan Gopaluni; Victor M. Zavala; James A. Olson (ACC, 2016)

Robust model-based delay timer alarm for non-linear processes. - Aditya Tulsyan; R. Bhushan Gopaluni (ACC, 2016)

Multiobjective economic model predictive control of mechanical pulping processes. - Hui Tian; Qiugang Lu; R. Bhushan Gopaluni; Victor M. Zavala (CDC, 2016)

Regularized maximum likelihood estimation of sparse stochastic monomolecular biochemical reaction networks. - Hong Jang; Kwang-Ki K. Kim; Richard D. Braatz; R. Bhushan Gopaluni; Jay H. Lee (Comput. Chem. Eng., 2016)

Particle filtering without tears: A primer for beginners. - Aditya Tulsyan; R. Bhushan Gopaluni; Swanand R. Khare (Comput. Chem. Eng., 2016)

A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects. - O. Vahidi; K. E. Kwok; R. Bhushan Gopaluni; F. K. Knop (Medical Biol. Eng. Comput., 2016)

Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines. - Qiugang Lu; Lee D. Rippon; R. Bhushan Gopaluni; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont (ACC, 2017)

Fault identification with modified reconstruction-based contribution based on kernel principal component analysis. - Koji Kitano; Manabu Kano; R. Bhushan Gopaluni (ASCC, 2017)

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty. - David S. Zamar; R. Bhushan Gopaluni; Shahab Sokhansanj; Nathaniel K. Newlands (Comput. Chem. Eng., 2017)

Performance Assessment of Cross-Directional Control for Paper Machines. - Qiugang Lu; Michael G. Forbes; R. Bhushan Gopaluni; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont (IEEE Trans. Control. Syst. Technol., 2017)

Locality preserving discriminative canonical variate analysis for fault diagnosis. - Qiugang Lu; Benben Jiang; R. Bhushan Gopaluni; Philip D. Loewen; Richard D. Braatz (Comput. Chem. Eng., 2018)

Application of neural networks for optimal-setpoint design and MPC control in biological wastewater treatment. - Mahsa Sadeghassadi; Chris J. B. Macnab; R. Bhushan Gopaluni; David T. Westwick (Comput. Chem. Eng., 2018)

A switching strategy for adaptive state estimation. - Aditya Tulsyan; Swanand R. Khare; Biao Huang 001; R. Bhushan Gopaluni; J. Fraser Forbes (Signal Process., 2018)

Sensing Concept for Practical Performance-Monitoring of Centrifugal Pumps. - Bryan Bohn; James A. Olson; R. Bhushan Gopaluni; Boris Stoeber (IEEE SENSORS, 2019)

Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes. - Kai Wang 024; Michael G. Forbes; R. Bhushan Gopaluni; Junghui Chen; Zhihuan Song (IEEE Access, 2019)

Identification of symmetric noncausal processes. - Qiugang Lu; Philip D. Loewen; R. Bhushan Gopaluni; Michael G. Forbes; Johan U. Backström; Guy Albert Dumont; Michael S. Davies (Autom., 2019)

Almost Surely Stable Deep Dynamics. - Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (NeurIPS, 2020)

Support vector machine approach for model-plant mismatch detection. - Qiugang Lu; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; Guy Albert Dumont; R. Bhushan Gopaluni (Comput. Chem. Eng., 2020)

A tractable approximation for stochastic MPC and application to mechanical pulping processes. - Hui Tian; Jagadeesan Prakash; Victor M. Zavala; James A. Olson; R. Bhushan Gopaluni (Comput. Chem. Eng., 2020)

Deep Reinforcement Learning for Process Control: A Primer for Beginners. - Steven Spielberg; Aditya Tulsyan; Nathan P. Lawrence; Philip D. Loewen; R. Bhushan Gopaluni (CoRR, 2020)

Reinforcement Learning based Design of Linear Fixed Structure Controllers. - Nathan P. Lawrence; Gregory E. Stewart; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2020)

Optimal PID and Antiwindup Control Design as a Reinforcement Learning Problem. - Nathan P. Lawrence; Gregory E. Stewart; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2020)

Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction. - Kai Wang 024; R. Bhushan Gopaluni; Junghui Chen; Zhihuan Song (IEEE Trans. Ind. Informatics, 2020)

Representation learning and predictive classification: Application with an electric arc furnace. - Lee D. Rippon; Ibrahim Yousef; Behrooz Hosseini; Arbi Bouchoucha; Jean-Francois Beaulieu; Carole Prévost; Michel Ruel; S. L. Shah 001; R. Bhushan Gopaluni (Comput. Chem. Eng., 2021)

A Meta-Reinforcement Learning Approach to Process Control. - Daniel G. McClement; Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2021)

Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning. - Nathan P. Lawrence; Michael G. Forbes; Philip D. Loewen; Daniel G. McClement; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2021)

Time-Variant Digital Twin Modeling through the Kalman-Generalized Sparse Identification of Nonlinear Dynamics. - Jingyi Wang 005; Jesús Moreira; Yankai Cao; R. Bhushan Gopaluni (ACC, 2022)

Soft Sensor Change Point Detection and Root Causal Analysis. - Liang Cao; R. Bhushan Gopaluni; Lim C. Siang; Yankai Cao; Jin Li (SICE, 2022)

Meta Reinforcement Learning for Adaptive Control: An Offline Approach. - Daniel G. McClement; Nathan P. Lawrence; Johan U. Backström; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni (CoRR, 2022)

Meta-Reinforcement Learning for Adaptive Control of Second Order Systems. - Daniel G. McClement; Nathan P. Lawrence; Michael G. Forbes; Philip D. Loewen; Johan U. Backström; R. Bhushan Gopaluni (CoRR, 2022)

Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey. - R. Bhushan Gopaluni; Aditya Tulsyan; Benoît Chachuat; Biao Huang 001; Jong Min Lee 002; Faraz Amjad; Seshu Kumar Damarla; Jong Woo Kim; Nathan P. Lawrence (CoRR, 2022)

Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics. - Lim C. Siang; Shams Elnawawi; Lee D. Rippon; Daniel L. O'Connor; R. Bhushan Gopaluni (CoRR, 2022)

Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system. - Tobi Michael Alabi; Nathan P. Lawrence; Lin Lu; Zaiyue Yang; R. Bhushan Gopaluni (CoRR, 2023)

A modular framework for stabilizing deep reinforcement learning control. - Nathan P. Lawrence; Philip D. Loewen; Shuyuan Wang; Michael G. Forbes; R. Bhushan Gopaluni (CoRR, 2023)

Reinforcement Learning with Partial Parametric Model Knowledge. - Shuyuan Wang; Philip D. Loewen; Nathan P. Lawrence; Michael G. Forbes; R. Bhushan Gopaluni (CoRR, 2023)

Process Monitoring Using Domain-Adversarial Probabilistic Principal Component Analysis: A Transfer Learning Framework. - Atefeh Daemi; R. Bhushan Gopaluni; Biao Huang 001 (IEEE Trans. Ind. Informatics, 2023)

Simultaneous digital twin identification and signal-noise decomposition through modified generalized sparse identification of nonlinear dynamics. - Jingyi Wang 005; Jesús Moreira; Yankai Cao; R. Bhushan Gopaluni (Comput. Chem. Eng., 2023)

Stable Soft Sensor Modeling for Industrial Systems. - Liang Cao; Yankai Cao; R. Bhushan Gopaluni (ICPS, 2024)

Guiding Reinforcement Learning with Incomplete System Dynamics. - Shuyuan Wang; Jingliang Duan; Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Lixian Zhang (IROS, 2024)

Deep Hankel matrices with random elements. - Nathan P. Lawrence; Philip D. Loewen; Shuyuan Wang; Michael G. Forbes; R. Bhushan Gopaluni (L4DC, 2024)

Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior. - Nathan P. Lawrence; Philip D. Loewen; Shuyuan Wang; Michael G. Forbes; R. Bhushan Gopaluni (Autom., 2024)

Machine learning for industrial sensing and control: A survey and practical perspective. - Nathan P. Lawrence; Seshu Kumar Damarla; Jong Woo Kim; Aditya Tulsyan; Faraz Amjad; Kai Wang 024; Benoît Chachuat; Jong Min Lee 002; Biao Huang 001; R. Bhushan Gopaluni (CoRR, 2024)

Drilling Process Monitoring Based on Operation Mode Recognition and Dynamic Feature Extraction. - Yupeng Li; Weihua Cao; R. Bhushan Gopaluni; Wenkai Hu; Chao Gan; Min Wu 002 (IEEE Trans. Ind. Electron., 2024)

Machine learning in process systems engineering: Challenges and opportunities. - Prodromos Daoutidis; Jay H. Lee; Srinivas Rangarajan; Leo Chiang; R. Bhushan Gopaluni; Artur M. Schweidtmann; Iiro Harjunkoski; Mehmet Mercangöz; Ali Mesbah 002; Fani Boukouvala; Fernando V. Lima; Ehecatl Antonio del Rio-Chanona; et al. (Comput. Chem. Eng., 2024)

From automated to autonomous process operations. - Michael Baldea; Apostolos T. Georgiou; R. Bhushan Gopaluni; Mehmet Mercangöz; Constantinos C. Pantelides; Kiran Sheth; Victor M. Zavala; Christos Georgakis 002 (Comput. Chem. Eng., 2025)

Time series representation learning via cross-domain predictive and contextual contrasting: Application to fault detection. - Ibrahim Yousef; Sirish L. Shah; R. Bhushan Gopaluni (Eng. Appl. Artif. Intell., 2025)

Comprehensive Analysis on Machine Learning Approaches for Interpretable and Stable Soft Sensors. - Liang Cao; Jingyi Wang 005; Jianping Su; Yi Luo; Yankai Cao; Richard D. Braatz; R. Bhushan Gopaluni (IEEE Trans. Instrum. Meas., 2025)

A view on learning robust goal-conditioned value functions: Interplay between RL and MPC. - Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Ali Mesbah 002 (CoRR, 2025)

DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation. - Shuyuan Wang; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Wei Pan (CoRR, 2025)